Abstract
In this paper, we present a comprehensive study and analysis of the Chan-Vese algorithm for image segmentation. We employ a discretized scheme derived from the empirical study of the Chan-Vese model's functional energy and its partial differential equation based on its level set function. We provide a proof of the results and an implementation using MATLAB. Leveraging modern computer vision methodologies, we propose a functional segmentation loss based on active contours, utilizing this http URL and a level set based on the Chan-Vese algorithm. We compare our results with common computer vision segmentation datasets and evaluate the performance of classical loss functions against our proposed method. All code and materials used are available at this https URL.
Abstract (translated)
在这篇论文中，我们对Chan-Vese算法进行了全面的研究和分析。我们采用了一种离散化方案，该方案基于对Chan-Vese模型功能能量的实证研究以及其水平集函数的部分微分方程得出。我们提供了结果证明，并使用MATLAB进行了实现。通过利用现代计算机视觉方法，我们提出了一种基于主动轮廓的功能分割损失，结合了这个URL和基于Chan-Vese算法的水平集。我们将我们的研究成果与常见的计算机视觉分割数据集进行比较，并评估经典损失函数与我们提出的方案之间的性能差异。所有使用的代码和材料都可在该https URL处获取。
URL
https://arxiv.org/abs/2508.19946
